The uptake of the organophosphates tris(2-chloroethyl) phosphate (TCEP), tris(1-chloro-2-propyl) phosphate (TCPP), tributyl phosphate (TBP), the insect repellant N,N-diethyl toluamide (DEET), and the plasticizer n-butyl benzenesulfonamide (NBBS) into plants was studied in greenhouse experiments and simulated with a dynamic physiological plant uptake model. The calibrated model was coupled to a tipping buckets soil transport model and a field scenario with sewage sludge application was simulated. High uptake of the polar, low-volatile compounds TCEP, TCPP, and DEET into plants was found, with highest concentrations in straw (leaves and stem). Uptake into carrot roots was high for TCPP and TBP. NBBS showed no high uptake but was rapidly degraded. Uptake into barley seeds was small. The pattern and levels of uptake could be reproduced by the model simulations, which indicates mainly passive uptake and transport (i.e., by the transpiration stream, with the water) into and within the plants. Also the field simulations predicted a high uptake from soil into plants of TCEP, TCPP, and DEET, while TBP is more likely taken up from air. The BCF values measured and calculated in the greenhouse study are in most cases comparable to the calculated values of the field scenario, which demonstrates that greenhouse studies can be suitable for predicting the behavior of chemicals in the field. Organophosphates have a high potential for bioaccumulation in crops and reach agricultural fields both via sewage sludge and by atmospheric deposition.

The objective of this review is to reflect on the multiple roles of bacteria in wastewater habitats with particular emphasis on their harmful potential for human health. Indigenous bacteria promote a series of biochemical and metabolic transformations indispensable to achieve wastewater treatment. Some of these bacteria may be pathogenic or harbour antibiotic resistance or virulence genes harmful for human health. Several chemical contaminants (heavy metals, disinfectants and antibiotics) may select these bacteria or their genes. Worldwide studies show that treated wastewater contain antibiotic resistant bacteria or genes encoding virulence or antimicrobial resistance, evidencing that treatment processes may fail to remove efficiently these bio-pollutants. The contamination of the surrounding environment, such as rivers or lakes receiving such effluents, is also documented in several studies. The current state of the art suggests that only some of antibiotic resistance and virulence potential in wastewater is known. Moreover, wastewater habitats may favour the evolution and dissemination of new resistance and virulence genes and the emergence of new pathogens. For these reasons, additional research is needed in order to obtain a more detailed assessment of the long-term effects of wastewater discharges. In particular, it is important to measure the human and environmental health risks associated with wastewater reuse.

Utilization of agrowaste materials for the production of activated carbon, as an excellent adsorbent with large surface area, is well established industrially, for dephenolation of wastewater. In the present work, dried pods of Prosopis cineraria—a novel and low-cost agrowaste material—were used to prepare activated carbons by zinc chloride activation. Batch adsorption experiments were carried out to study the effects of various physicochemical parameters such as initial phenol concentration, adsorbent dose, initial solution pH, and temperature. Pseudo-first-order second-order and diffusion kinetic models were used to identify the possible mechanisms of such adsorption process. The Langmuir and Freundlich equations were used to analyze the adsorption equilibrium. Maximum removal efficiency of 86 % was obtained with 25 mg L⁻¹ of initial phenol concentration. The favorable pH for maximum phenol adsorption was 4.0. Freundlich equation represented the adsorption equilibrium data more ideally than the Langmuir. The maximum adsorption capacity obtained was 78.32 mg g⁻¹ at a temperature of 30 °C and 25 mg L⁻¹ initial phenol concentration. The adsorption was spontaneous and endothermic. The pseudo-second-order model, an indication of chemisorption mechanism, fitted the experimental data better than the pseudo-first-order Lagergren model. Regeneration of spent activated carbon was carried out using Pseudomonas putida MTCC 2252 as the phenol-degrading microorganism. Maximum regeneration up to 57.5 % was recorded, when loaded phenol concentration was 25 mg L⁻¹. The data obtained in this study would be useful in designing and fabricating an efficient treatment plant for phenol-rich effluents.

The effects of solution pH on adsorption of trace metals to different types of natural aquatic solid materials have been studied extensively, but few studies have been carried out to investigate the effect of pH at which the solid materials were formed on the adsorption. The purpose of present study is to examine this effect of culture pH on metal adsorption to natural freshwater biofilms. The adsorption of Pb and Cd to biofilms which were developed at different culture pH values (ranging from 6.5 to 9.0) was measured at the same adsorption pH value (6.5). The culture pH had considerable effects on both composition and metal adsorption ability of the biofilms. Higher culture pH usually promoted the accumulation of organic material and Fe oxides in the biofilms. The culture pH also affected the quantity and species of algae in the biofilms. The adsorption of Pb and Cd to the biofilms generally increased with the increase of culture pH. This increase was minor at lower pH range and significant at higher pH range and was more remarkable for Cd adsorption than for Pb adsorption. The notable contribution of organic material to the adsorption at higher culture pH values was also observed. The profound impacts of culture pH on adsorption behavior of biofilms mainly resulted from the variation of total contents of the biofilm components and were also affected by the alteration of composition and properties of the components.

In urban environments, human exposure to air pollutants is expected to be significantly increased, especially near busy traffic streets, street canyons, tunnels, etc. where urban topography and microclimate may additionally cause poor air conditions giving rise to pollution hotspots. As a practical and cost-effective approach, active moss biomonitoring survey of some major and trace element air pollution was performed in the Belgrade street canyons and city tunnel in 2011 with the aim to evaluate possibility of using Sphagnum girgensohnii moss bags for investigation of the small-scale vertical and horizontal distribution patterns of the elements. In five street canyons, the moss bags were hung at heights of about 4, 8 and 16 m, during 10 weeks, and also, for the same time, the moss bags were exposed in the tunnel, in front of and out of it. After the exposure period, the concentrations of Al, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, V and Zn in the moss were determined by inductively coupled plasma optical emission spectrometry. According to the results, in all street canyons, the vertical distribution patterns of the moss elements concentration (Al, Ba, Co, Cr, Cu, Ni, Pb, Sr, V and Zn) showed statistically significant decrease from the first to the third heights of bags exposure. In the tunnel experiment, from inner to out of the tunnel, for Al, Ba, Cd, Co, Cr, Cu, Fe, K and Zn, decreasing trend of concentrations was obtained. Significantly higher concentration of the elements was pronounced for the tunnel in comparison with the street canyons. The results indicate that the use of S. girgensohnii moss bags is a simple, sensitive and inexpensive way to monitor the small-scale inner city spatial distribution of airborne major and trace element content.

The capability of a moving bed biofilm reactor (MBBR) to remove the iodinated contrast media (ICM) iohexol (IOX) and diatrizoate (DTZ) from municipal wastewater was studied. A selected number of clones of microorganisms present in the biofilm were identified. Biotransformation products were tentatively identified and the toxicity of the treated effluent was assessed. Microbial samples were DNA-sequenced and subjected to phylogenetic analysis in order to confirm the identity of the microorganisms present and determine the microbial diversity. The analysis demonstrated that the wastewater was populated by a bacterial consortium related to different members of Proteobacteria, Firmicutes, and Nitrisporae. The optimum removal values of the ICM achieved were 79 % for IOX and 73 % for DTZ, whereas 13 biotransformation products for IOX and 14 for DTZ were identified. Their determination was performed using ultra-performance liquid chromatography–tandem mass spectrometry. The toxicity of the treated effluent tested to Daphnia magna showed no statistical difference compared to that without the addition of the two ICM. The MBBR was proven to be a technology able to remove a significant percentage of the two ICM from urban wastewater without the formation of toxic biodegradation products. A large number of biotransformation products was found to be formed. Even though the amount of clones sequenced in this study does not reveal the entire bacterial diversity present, it provides an indication of the predominating phylotypes inhabiting the study site.

The utilization of sustainable and biodegradable lignocellulosic fiber to detoxify the noxious Cr(VI) from wastewater is considered a versatile approach to clean up a contaminated aquatic environment. The aim of the present research is to assess the proficiency and mechanism of biosorption on Ficus carica bast fiber via isotherm models (Langmuir, Freundlich, Temkin, Harkin’s–Jura, and Dubinin–Radushkevich), kinetic models, and thermodynamic parameters. The biomass extracted from fig plant was characterized by scanning electron microscopy and Fourier-transform infrared spectroscopy. To optimize the maximum removal efficiency, different parameters like effect of initial concentration, effect of temperature, pH, and contact time were studied by batch method. The equilibrium data were best represented by the Langmuir isotherm model, and the maximum adsorption capacity of Cr(VI) onto biosorbent was found to be 19.68 mg/g. The pseudo-second-order kinetic model adequately described the kinetic data. The calculated values of thermodynamic parameters such as enthalpy change (∆H ⁰), entropy change (∆S ⁰), and free energy change (∆G ⁰) were 21.55 kJ/mol, 76.24 J/mol K, and −1.55 kJ/mol, respectively, at 30 °C which accounted for spontaneous and endothermic processes. The study of adsorbent capacity for Cr(VI) removal in the presence of Na⁺, Mg²⁺, Ca²⁺, SO ₄ ²⁻ , HCO ₃ ⁻ and Cl⁻ illustrated that the removal of Cr(VI) increased in the presence of HCO³⁻ ions; the presence of Na⁺, SO ₄ ²⁻ or Cl⁻ showed no significant influence on Cr(VI) adsorption, while Ca²⁺ and Mg²⁺ ions led to an insignificant decrease in Cr(VI) adsorption. Further, the desorption studies illustrated that 31.10 % of metal ions can be removed from an aqueous system, out of which 26.63 % of metal ions can be recovered by desorption in first cycle and the adsorbent can be reused. The results of the scale-up study show that the ecofriendly detoxification of Cr(VI) from aqueous systems was technologically feasible.

With the filling of the Three Gorges Reservoir, original vegetation in the water level fluctuation zone (WLFZ) between the elevations of 145 and 175 m disappeared due to the reversal of submergence time (winter flooding) and prolonged inundation duration (nearly half a year). To better understand the relationships between the environmental factors and recovered plant communities for reconstructing floristically diverse riparian zone, we conducted a field survey in 11 sites in the WLFZ in June 2010, and vegetation composition, flooding characteristics, heavy metals, and soil major nutrients were determined. Consequently, the canonical correspondence analysis was used to investigate the relationships between plant species composition and flooding characteristics, heavy metal contamination, and soil nutrients. Results demonstrated that vegetation in the WLFZ was dominated by annuals, i.e., Echinochloa crusgalli and Bidens tripartita, and perennials including Cynodon dactylon, and plant species richness and diversity were negatively associated with flooding duration, heavy metal contamination, and nutrients including total phosphorus, available phosphorus, available potassium, and nitrate. Our results suggest that plant species, recovering mainly through soil seed bank and regeneration of remnant individuals, have been influenced by the combined effects of environmental factors.

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NOx), nitrogen dioxide (NO2), nitrogen monoxide (NO), ozone (O3), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM10) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R (2) of more than 0.82 between modeled and observed hourly pollutant levels for CO, NOx, NO2, NO, and PM10. However, predicted O3 levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.

The discharges of uranium and associated radionuclides as well as heavy metals and metalloids from waste and tailing dumps in abandoned uranium mining and processing sites pose contamination risks to surface and groundwater. Although many more are being planned for nuclear energy purposes, most of the abandoned uranium mines are a legacy of uranium production that fuelled arms race during the cold war of the last century. Since the end of cold war, there have been efforts to rehabilitate the mining sites, initially, using classical remediation techniques based on high chemical and civil engineering. Recently, bioremediation technology has been sought as alternatives to the classical approach due to reasons, which include: (a) high demand of sites requiring remediation; (b) the economic implication of running and maintaining the facilities due to high energy and work force demand; and (c) the pattern and characteristics of contaminant discharges in most of the former uranium mining and processing sites prevents the use of classical methods. This review discusses risks of uranium contamination from abandoned uranium mines from the biogeochemical point of view and the potential and limitation of uranium bioremediation technique as alternative to classical approach in abandoned uranium mining and processing sites.